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Record W4402206715 · doi:10.1007/s10460-024-10609-9

“New food cultures” and the absent food citizen: immigrants in urban food policy discourse

2024· article· en· W4402206715 on OpenAlexfundno aff
Isabela Bonnevera

Bibliographic record

VenueAgriculture and Human Values · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicOrganic Food and Agriculture
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research CouncilUniversitat Autònoma de Barcelona
KeywordsImmigrationEnvironmental sociologyFood systemsSociologyPolitical scienceEconomic growthFood securitySocial scienceEconomicsGeographyAgriculture

Abstract

fetched live from OpenAlex

Abstract Multicultural cities in the Global North are rapidly developing and releasing urban food policies that outline municipal visions of sustainable food systems. In turn, these policies shape conceptions of food citizenship in the city. While these policies largely absorb activities previously associated with “alternative” food systems, little is known about how they respond to critical food and race scholars who have noted that these food practices and spaces have historically marginalized immigrants. A critical discourse analysis of 22 urban food policies from Global North cities reveals that most policies do not meaningfully consider immigrant foodscapes, foodways, and food-related labour. Many promote hegemonic and/or ethno-nationalistic understandings of “healthy” and “sustainable” food without recognizing immigrants’ food-related knowledge and skills. Policies largely fail to connect the topic of immigrant labour with goals like shortening supply chains, subject immigrant neighbourhoods to stigmatizing health discourses, and lack acknowledgement of the barriers immigrants may face to participating in sustainable food systems. Relatedly, policy discourses articulate forms of food citizenship that emphasize individual obligations over rights related to food. This jeopardizes the potential for immigrants to be seen as belonging to dominant political urban food communities and benefitting from the symbolic and material rewards associated with them.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.587
Threshold uncertainty score0.550

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.233
Teacher spread0.223 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2024
Admission routes1
Has abstractyes

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